Evidence map›Paper›PMID 41181338›Full record

ReviewSage open pediatrics

Neonatal Sepsis in Low-Resource Emergency Settings: Evidence-Based Strategies for Early Recognition and Management.

Salma Tamer Abdelrahman, Nourhan M Kamal, Sohaila Mohamed Mohamed Abdelbar, Rana Al Juhmani, Chibuike Daniel Onyejesi, Almotazbellah Attalla, Mohammed Alsabri

Abstract readReview
In one paragraph

Review in Sage open pediatrics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Salma Tamer AbdelrahmanZagazig University, Egypt.ORCID https://orcid.org/0009-0007-9896-3946
Nourhan M KamalInstitue of Global Health and Human Ecology-The American University in Cairo, Cairo, Egypt.ORCID https://orcid.org/0009-0009-8815-0233
Sohaila Mohamed Mohamed AbdelbarKasr Al-Ainy Medical School, Cairo University, Egypt.
Rana Al JuhmaniBaskent University, Ankara, Türkiye.
Chibuike Daniel OnyejesiGbeye Hospital & Maternity, Rivers State, Nigeria.
Almotazbellah AttallaAlexandria University, Egypt.
Mohammed AlsabriChristopher's Hospital, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-7278-2289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review highlights challenges in recognition, diagnosis, and management of neonatal sepsis in low-resource emergency settings. It discusses actionable, resource-adapted strategies to reduce neonatal morbidity and mortality. A comprehensive literature review was conducted using peer-reviewed research articles and global health guideline addressing neonatal sepsis. Neonatal sepsis is the leading cause of newborn deaths, with low- and middle-income countries accounting for 99% of cases. Since limited access to blood cultures, biomarker testing, and antibiotic availability delay diagnosis and management. Furthermore, antimicrobial resistance, poor infection control, and socioeconomic barriers worsen outcomes. However, emerging interventions including Point of care diagnostics, Kangaroo Mother Care, telemedicine, and artificial intelligence-based technologies demonstrate effectiveness. Early recognition and evidence-based management should be supported through affordable, feasible diagnostics, refined antibiotic use, and strengthened health infrastructure. Future initiatives must focus on innovations and international collaborations aimed at enhancing neonatal survival and health.

Indexed as

antimicrobial resistanceartificial intelligenceemergency carekangaroo mother carelow-resource settingsneonatal sepsis

Identifiers

PMID41181338
PMCPMC12576100

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.